Results:

Results indicated that the association of education with improved cognitive test scores is not mediated by g, but consists of direct effects on specific cognitive skills. These results suggest a decoupling of educational gains from increases in general intellectual capacity.

Highlights:

https://en.wikipedia.org/wiki/G_factor_(psychometrics) The g factor (also known as general intelligence, general mental ability or general intelligence factor) is a construct developed in psychometric investigations of cognitive abilities and human intelligence. It is a variable that summarizes positive correlations among different cognitive tasks, reflecting the fact that an individual’s performance on one type of cognitive task tends to be comparable to that person’s performance on other kinds of cognitive tasks. The g factor typically accounts for 40 to 50 percent of the between-individual performance differences on a given cognitive test, and composite scores (“IQ scores”) based on many tests are frequently regarded as estimates of individuals’ standing on the g factor.[1] The terms IQ, general intelligence, general cognitive ability, general mental ability, or simply intelligence are often used interchangeably to refer to this common core shared by cognitive tests.[2]

We conducted structural equation modeling on data from a large (n 1,091), longitudinal sample, with a measure of intelligence at age 11 years and 10 tests covering a diverse range of cognitive abilities taken at age 70.

There is evidence supporting the view that education has a positive, causal effect on cognitive ability. Ceci (1991) provided an extensive review. For example, he discussed a study showing that men in a Swedish sample (n 4,616) with shorter educational durations had lower IQ scores at age 18 years on a military service qualification test than those with matched age 13 IQ scores and similar socioeconomic statuses who stayed in school for longer (H盲rnqvist, 1968). In addition, he described a study by Cahan and Cohen (1989) that used a regression-discontinuity design in a sample of around 11,000 students to show that the slopes of IQ increases across school grades are discontinuous, indicating that education improves cognitive ability above and beyond the general effects of maturation. On the basis of these and a large number of other studies, Ceci (1991) concluded that “schooling emerges as an extremely important source of variance” in IQ test performance (p. 719).

This number was broadly concurrent with a later study by Falch and Sandgren Massih (2011) that analyzed data from the Malm枚 Longitudinal Study (initial n 1,547). They found that, controlling for ability at age 10, education improved IQ, measured on a test designed to be similar to the early measure, by 2.9 to 3.5 points per year by age 20.

this does not exclude the possibility of reverse causality or confounding, because individuals were not randomized to receive more or less education

Two recent studies using quasi-experimental designs were able to address the weaknesses of the previous literature. First, Brinch and Galloway (2012) utilized data spanning a period of significant educational reform in Norway to examine the effect of exposure to schooling in adolescence on subsequent IQ. Across the years 1955 to 1972, the Norwegian government raised the compulsory duration of schooling by 2 years (from 7 to 9 years in total). This reform was not implemented at the same time in all administrative areas, and the timing of the reform by area was essentially at random. Thus, students in the areas where educational duration was increased could be compared to those in areas where they were able to leave school at the earliest opportunity. The effects of these reforms on later ability were assessed using IQ data from an examination taken on entrance to compulsory military service at age 19 (for this reason, data were available only for men). Using two alternative econometric analyses (difference-indifference and instrumental variables) on a sample of over 100,000 individuals, Brinch and Galloway (2012) estimated the benefit of 1 year of schooling at 3.7 IQ points on average.

On the basis of the literature discussed earlier, a relatively strong case can be made that exposure to education improves cognitive ability. However, these studies leave open the question of what, precisely, is being improved. Because typical IQ tests assess a wide variety of cognitive skills, IQ score increases could reflect the sum of improvements on specific cognitive abilities. For example, in the course of education, a student may learn the definitions of words, leading to better scores on vocabulary subtests in IQ test batteries

Here, we report an analysis of a longitudinal cohort (the Lothian Birth Cohort 1936) of over 1,000 individuals across a follow-up period of almost 60 years with intelligence measurements from both early and late in life. We investigated whether education is associated with relative improvements in the g factor extracted from a battery of 10 diverse cognitive tests (domain-general effects of education on cognitive development), or with improvements on only some of those tests (domain-specific effects of education). An advantage of the dataset used here is that we were able to build models of very long-term, lasting effects of education on lifetime cognitive development.

The three possibilities we tested are illustrated by Models A, B, and C in Figure 1. All models control for prior intelligence, measured at age 11 years, before there was any major variation in educational duration in our sample. Higher childhood intelligence is hypothesized to predict both longer educational duration and higher g-factor scores in later life; these relationships are shown in the upper part of each model. In Model A, education is hypothesized to be associated with the subtests via the latent general factor, g, extracted from them. Model B, which also includes a path from education to g, is similar to Model A, except that it adds some specific associations between education and individual cognitive test scores. This model suggests that education raises all cognitive capabilities via g, but also, beyond these benefits, confers additional improvements on some specific tests. Finally, in Model C, education is hypothesized to be associated with the subtests via only domain-specific paths. Model C suggests that it is this direct improvement in some-potentially all-subtests that is reflected in the IQ score improvements found in previous studies (e.g., Brinch & Galloway, 2012), but that these specific improvements do not transfer to increases in general intelligence. We tested which models had better fit and predicted that, if education improves intelligence by raising g, either or both of Models A and B would have significantly better fit to the data than Model C.

We then compared Model C to the previous models. It had significantly better fit than both Model A and Model B. Therefore, the model that had no path from education to g, and had only direct education-subtest paths, had significantly better fit to the data than the models in which education indirectly affected the intelligence subtests via g, regardless of whether they also included some direct paths from education to the subtests. Thi

A similar decoupling of IQ scores and g has been discussed in the context of the Flynn effect, the well-studied secular trend of increasing intelligence test scores across the 20th and 21st centuries (e.g., Flynn, 2009). A recent meta-analysis by te Nijenhuis and van der Flier (2013) concluded that the specific abilities shown to be improving across time tend to be those with lower g loadings. Our findings are consistent with the notion that increased compulsory education is one of the potential mechanisms of the Flynn effect (e.g., R枚nnlund & Nilsson, 2008): Whereas education raises IQ scores, it-like the Flynn effect- does not appear to improve g. The independence from general ability of increases (and decreases) in IQ scores across time, and between groups, is included in the model proposed by Flynn (2009).